Abstract: A method for device visualization includes receiving a set of physical characteristics including a description of spatial relationships of a plurality of markers within a device. Radiographic data of the device within a subject is acquired. An approximate location of each of the plurality of markers is identified within the radiographic data. A trajectory function is constructed for the device within the subject based on the identified approximate locations of each of the markers and the received set of physical characteristics. A section function is constructed for the device based on the set of physical characteristics and a 3D model is generated for the device based on the constructed trajectory function and the section function. A rendering of the 3D model is displayed on a display device.

Abstract: A method for the detection of a balloon catheter within a fluoroscopic image, including: removing noise from a fluoroscopic image; detecting edges of a balloon catheter in the fluoroscopic image, wherein the detected edges include subsets of connected edges; extracting an edge subset from the subsets of connected edges; fitting a model to the extracted edge subset; removing outliers of the extracted edge subset based on the fitting of the model; adding the extracted edge subset without the outlier to a data set; repeating the extracting, fitting, removing and adding steps for the remainder of the subsets of connected edges; and fitting the model to the data set, wherein the data set is indicative of the balloon catheter.

Abstract: Localization of a coil is provided for magnetic resonance (MR)-guided intervention. A multi-scale decomposition and characteristic transitions in the power spectra for the coil are used to determine a distribution of likelihood of the coil being at each of various locations and/or to determine a confidence in the position determination. For example, the power spectra along each axis is used to generate a likelihood distribution of the location of the coil. The power spectra are decomposited at different scales. For each scale, the modulus maxima reflecting transitions in the power spectra are matched using various criteria. A likelihood is calculated for each of the matched candidates from characterizations of the matched candidates. The likelihood distribution is determined from a combination of the likelihoods from the various scales.

Abstract: A method including receiving a first two-dimensional (2D) image; and applying a filter to the 2D image to produce a filtered image that identifies a circular object of interest, wherein the filter is based on the integral sum of the function S, where the filter output at point x is M ? ( x ) = ? ? y ? V ? ? S ? ( m , ? , r , y ) ? ? ? ? y which is obtained from the 2D image, the function S is represented by S(m,?,r,y)=S1(m)S2(?,r), where m is a magnitude of a gradient at location y, r is a radial distance from y to x, and ? is an angle between the gradient at location y and the radial distance from y to x, S 1 ? ( m ) = ( tan - 1 ? ( m - C 1 ) + ? 2 ) ? , ? s 2 ? ( ? , r ) = 1 ? ? 2 ? ? ? ? ? - ( r × sin ? ? ? ) 2 2 ? ? ? 2 × ? - r × sin ? ( 90 - ? ) C 2 - r × sin ? ( 90 - ? ) ? 1 ? ? 2 ? ? ? ? ? - x 2 2 ? ? ? 2 ? ? ? x , C1 depend

Abstract: A method for device visualization includes receiving a set of physical characteristics including a description of spatial relationships of a plurality of markers within a device. Radiographic data of the device within a subject is acquired. An approximate location of each of the plurality of markers is identified within the radiographic data. A trajectory function is constructed for the device within the subject based on the identified approximate locations of each of the markers and the received set of physical characteristics. A section function is constructed for the device based on the set of physical characteristics and a 3D model is generated for the device based on the constructed trajectory function and the section function. A rendering of the 3D model is displayed on a display device.

Abstract: Localization of a coil is provided for magnetic resonance (MR)-guided intervention. A multi-scale decomposition and characteristic transitions in the power spectra for the coil are used to determine a distribution of likelihood of the coil being at each of various locations and/or to determine a confidence in the position determination. For example, the power spectra along each axis is used to generate a likelihood distribution of the location of the coil. The power spectra are decomposited at different scales. For each scale, the modulus maxima reflecting transitions in the power spectra are matched using various criteria. A likelihood is calculated for each of the matched candidates from characterizations of the matched candidates. The likelihood distribution is determined from a combination of the likelihoods from the various scales.

Abstract: A method for the detection of a balloon catheter within a fluoroscopic image, including: removing noise from a fluoroscopic image; detecting edges of a balloon catheter in the fluoroscopic image, wherein the detected edges include subsets of connected edges; extracting an edge subset from the subsets of connected edges; fitting a model to the extracted edge subset; removing outliers of the extracted edge subset based on the fitting of the model; adding the extracted edge subset without the outlier to a data set; repeating the extracting, fitting, removing and adding steps for the remainder of the subsets of connected edges; and fitting the model to the data set, wherein the data set is indicative of the balloon catheter.

Abstract: A method including receiving a first two-dimensional (2D) image; and applying a filter to the 2D image to produce a filtered image that identifies a circular object of interest, wherein the filter is based on the integral sum of the function S, where the filter output at point x is M ? ( x ) = ? ? y ? V ? ? S ? ( m , ? , r , y ) ? ? ? ? y which is obtained from the 2D image, the function S is represented by S(m,?,r,y)=S1(m)S2(?,r), where m is a magnitude of a gradient at location y, r is a radial distance from y to x, and ? is an angle between the gradient at location y and the radial distance from y to x, S 1 ? ( m ) = ( tan - 1 ? ( m - C 1 ) + ? 2 ) ? , ? s 2 ? ( ? , r ) = 1 ? ? 2 ? ? ? ? ? - ( r × sin ? ? ? ) 2 2 ? ? ? 2 × ? - r × sin ? ( 90 - ? ) C 2 - r × sin ? ( 90 - ? ) ? 1 ? ? 2 ? ? ? ? ? - x 2 2 ? ? ? 2 ? ? ? x , C1 depends